The past few years have witnessed an exponential increase in the amount of searchable information available to users of knowledge management systems. Unfortunately, the tools for providing access to the volume of available information have not improved at the same pace at which the amount of information available has increased.
The tools provided to facilitate information access by users are structured on a query paradigm in which the user provides a search query containing a nominally complete listing of the available information related to the user's query prior to any attempt to search for information. In that paradigm, the user enters a complete query. The complete query is then sent from a client to a database. The database to which the query is sent is typically located on a remote server. A search is run against an entire database index. Results are returned to the client.
The current query paradigm presents several problems and associated resource costs. First, sending a search query to a remote server generates delay as the query traverses the network. Such delays vary with environment. In customer relationship management application, such a delay can prove particularly irksome when the user is forced to communicate over high-latency communication links, such as those frequently encountered by mobile users at the customer site. Second, running a search query against an entire database index generates delay as the query is processed against the index by the server. In customer relationship management application, such a delay can prove particularly irksome in situations where the user communicates with the database at a peak busy hour. Third, a paradigm that encourages the user to enter excessive amounts of data for a “complete” query wastes user time on data entry. Fourth, the results fail to leverage recurring patterns in user input and selection. All of these problems result in wasted time. Wasted time creates a directly calculable financial cost. All of these problems have the potential to decrease user satisfaction. Decreased user satisfaction results in costs that are harder to measure but can be more profound in the long term.